Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Detección de olores arquitectónicos× | Métricas de Complejidad del Software× | |
|---|---|---|
| Campo | Ingeniería de software | Ingeniería de software |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 2009 | 1976 |
| Autor original≠ | Martin Fowler and García et al. | Thomas J. McCabe |
| Tipo≠ | pattern-based analysis | quantitative measurement |
| Fuente seminal≠ | Fowler, M. (2018). Code smell. Martin Fowler's Website. link ↗ | McCabe, T. J. (1976). A complexity measure. IEEE Transactions on Software Engineering, 2(4), 308–320. DOI ↗ |
| Alias≠ | design smell detection, architectural debt analysis, system quality assessment | code complexity analysis, complexity measurement |
| Relacionados | 4 | 4 |
| Resumen≠ | Architecture smells are recurring patterns in system structure that indicate potential design problems. Introduced by García et al. (2009), these patterns signal violations of architectural principles (modularity, independence, abstraction) at system scale. Detection combines code metrics, dependency analysis, and pattern recognition to identify smells early, guiding refactoring and architectural improvements. | Software complexity metrics quantify the structural and operational difficulty of code through numerical measurements. Introduced by Thomas McCabe in 1976, cyclomatic complexity became the foundational approach. These metrics assess maintainability, testability, and defect risk, enabling teams to identify problematic code regions and guide refactoring efforts. |
| ScholarGateConjunto de datos ↗ |
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